427 Goddard Labs
Yunshu Fan, from the Ding and Gold Labs, is presenting a 2-part workshop to introduce the drift-diffusion model (DDM), a model that is commonly used in modeling decision behavior. The goals are to familiarize participants with the model enough to (1) start to think about whether and when the model can be usedful, and (2) feel less confused when reading about it in literature and talks.
To make the learning process more interactive and relevant please bring your computer to the sessions, as there will be code provided to play with the model.
The June 18th session will cover:
What is DDM? How DDM works conceptually, and some nomenclature issues
How to simulate DDM in MATLAB, using the random-dot motion discrimination task as an example
What does each parameter mean behaviorally/conceptually? Why do we model it this way? And, how to generate hypotheses to test.
Modifications to the basic DDM, including collapsing bound, biases, leaky integration, discounting some evidence, etc.
How to fit behavior to the model (if there is time and interest)